Wearable devices like smartwatches and smart wristbands have gained substantial
popularity in recent years. However, their small interfaces create inconvenience and limit …

Machine learning-based wearable human activity recognition (WHAR) models enable the
development of various smart and connected community applications such as sleep pattern …

Abstract Supervised Deep Learning (DL) models are currently the leading approach for
sensor-based Human Activity Recognition (HAR) on wearable and mobile devices …

Smart home systems contain plenty of features that enhance wellbeing in everyday life
through artificial intelligence (AI). However, many users feel insecure because they do not …

Abstract In recent times, Deep Neural Networks (DNNs) have been effectively used to tackle
various tasks such as emotion recognition, activity detection, disease prediction, and surface …

Smart infrastructures often intend to provide personalized context-aware services for their
residents. These context-aware services, in turn, often rely on sophisticated machine …

The ubiquitousness of smart and wearable devices with integrated acoustic sensors in
modern human lives presents tremendous opportunities for recognizing human activities in …

In recent years, non-invasive human activity recognition (HAR) has gathered huge
momentum using locomotive sensors. However, for effective HAR, there is a need for a …

Complex activities of daily living (ADLs) often consist of multiple micro-activities. When
performed sequentially, these micro-activities help the user accomplish the broad macro …

Augmented Reality (AR) is a growing topic of interest in HCI research. The emerging use of
AR is already bringing impacts to society and various individuals. AR gaming has been …